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How Sales Data Empowers Every Member of your Sales Team

Let’s face it, sales has never been easy.

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Understanding sales data can unlock a world of potential for any sales team. With buyers turning to digital experiences for self-discovery, the power of data has become undeniable. As these digital natives make purchasing decisions, sales leaders must adapt quickly to stay ahead of the curve. The key to this adaptation? Robust comprehension of sales data.

Sales data isn’t just numbers on a spreadsheet — it’s a guide to buyer behavior, preferences, and potential opportunities. Leveraging data enables sales teams to pinpoint qualified leads, close deals, and, ultimately, increase revenue. No longer are sales strategies dictated by guesswork or instinct alone.

In this article, we’ll walk you through everything you need to know about sales data. Discover sales data’s power and learn how to transform raw data into a robust sales strategy that meets the needs of modern B2B buyers.

How Do You Find Sales Data?

Sales data is the detailed records of your sales activities. It’s everything from the units sold, revenue generated, the time and location of each sale, buyer details, and much more. It’s the “who,” “what,” “when,” “where,” and “how” of your sales.

One of the primary sources of sales data is your own internal records. Suppose you’re selling a product or service. In that case, you’re already creating sales data records every day: invoices, order forms, receipts, and other sales transaction documents. They’re raw and instantly accessible data.

A Customer Relationship Management (CRM) system is another main source of sales data. This platform is designed to automatically record, organize, and analyze information about buyers and prospects. It helps you track buyers’ interactions, follow sales progress, and identify patterns over time. The beauty of a CRM system is that it stores data and allows you to draw actionable insights in real time.

You can also find sales data in market research reports conducted by professional research firms. These reports offer broad industry trends and competitor analyses, helping you understand your industry’s landscape and providing benchmarks to evaluate your sales performance.

Each of these sources offers unique insights and advantages. So you should consider using them in combination to comprehensively understand your business, competitors, and industry landscape. The more accurate sales data you can access, the better decisions you can make.

The Five Types of Sales Data

Below are five key types of data every sales team should be familiar with.

1. Demographic Data

Think of demographic data as the identity card of individual buyers. Demographic data includes a buyer’s details, such as their age, gender, location, and income level. It can help you paint a picture of who your customers are and what their needs might be. With this insight, you can segment your audiences into different segments and create more tailored sales and marketing strategies.

2. Firmographic Data

Firmographic data is the demographic data of businesses. It refers to the characteristics of the companies you’re targeting, including company size, industry, location, and revenue. Firmographic data is critical for B2B sales.

3. Technographic Data

Technographic data indicates the technology and tools used by your potential customers.

Let’s say you’re selling software products, and you know a prospect is already using your competitor’s solution. In this case, you can offer the prospect a more personalized package or emphasize how your product integrates seamlessly with their existing tech stack.

4. Chronographic data

Chronographic data is time-related information about your buyers. This can include purchase history, frequency of orders, and the stage of the customer lifecycle. Understanding this data will help you create timely sales and marketing strategies to target prospects at the right time and place.

5. Intent Data

Intent data is information about a prospect’s online activities that signal their potential purchase intent. It can be first-party (data you collect yourself) and third-party (data collected through a third-party platform).

Say a prospect visits your website and downloads your brochure. This suggests a possible buying intention. Based on that insight, you can tailor outreach strategies, prioritize leads, and improve overall sales effectiveness.

How is Sales Data Used?

Sales data benefits your sales team in many ways. Here’s how.

1. Understand Buyers’ Behavior

You can use sales data to categorize buyers based on company size, purchase history, or frequency of orders. This segmentation can lead to more targeted marketing and sales strategies, improving overall efficiency and success rates.

Sales data analysis can also highlight opportunities for upselling (encouraging the purchase of a higher-end product) or cross-selling (promoting related or complementary products). For instance, if buyers consistently purchase a particular product, they may be open to buying a premium version or related add-on services.

2. Identifying New Opportunities

Sales data can reveal new opportunities through trend analysis. This involves tracking sales patterns over time to spot trends or shifts in customer behavior.

For example, if a certain product’s sales have been steadily increasing month over month, that could signal a rising demand your team could capitalize on. Similarly, a sudden drop in sales could indicate a problem that needs to be addressed.

3. Optimizing the Sales Process

Sales data enables you to identify patterns and trends among top-performing reps. For example, by looking at the number of client visits each rep makes, you can determine the proportion of their time spent on value-added selling that contributes to closing sales. You can also track data to understand how reps collaborate with each other and who needs more support.

With these insights, you can formulate a more effective sales process. You can decide how best to allocate time and resources. Should reps make more client visits? Should they focus more on value-added selling? Should they collaborate more? Sales data allows you to answer these questions with confidence.

4. Improve Lead Generation

As said above, sales data can provide valuable insights into buyer behavior. This can involve understanding preferences and buying patterns and identifying the most popular products or services. Studying these patterns allows you to focus your lead generation efforts on prospects who are likely to have similar interests.

Sales data can also help fine-tune your outreach strategy. It can highlight the most effective times, platforms, and communication styles for reaching potential buyers. Knowing when and how to reach out to leads increases the chances of engagement and conversion.

5. Better Match People to Deals

By analyzing historical sales data, you can uncover patterns and trends related to each sales rep’s strengths and weaknesses.

For example, some reps may excel in certain industries, with specific product lines, or in specific geographical regions. Others might be good at closing large deals, while some could be exceptional at nurturing long-term relationships. By understanding these nuances, you can assign leads and opportunities to the reps most likely to close them.

Examples of Sales Data

Let’s take a look at some examples of sales data:

Software as a Service (SaaS)

Imagine you’re running a SaaS company that provides project management tools. Sales data in this context could be the following:

  • New subscriptions: The number of new customers who have signed up for your service in a given period.
  • Churn rate: The rate at which customers stop subscribing to your service.
  • Average revenue per user (ARPU): The average revenue generated per user or customer.
  • Conversion rates: The percentage of potential customers who complete a desired action, such as signing up for a free trial or converting to a paid plan.
  • Upgrade/Downgrade rates: The rate at which customers upgrade or downgrade their service plan.
  • Revenue growth rate: The rate at which your company’s revenue increases or decreases over a specific period.
  • Product usage data: How often and in what ways customers are using your software.

Finance Industry

Sales data in a financial institution can come in various forms, such as:

  • New accounts opened: The number of new savings, checking, investment, or credit accounts opened within a certain period.
  • Loan origination data: Details about the number, type, and value of loans originated.
  • Customer demographics: Information about the customers, such as age, income level, occupation, etc.
  • Customer segmentation data: Information on different customer segments like high-net-worth individuals, small businesses, etc.
  • Product and service usage data: Information on how customers use the bank’s products and services, such as frequency of transactions, average transaction size, etc.
  • Branch and online transaction data: Data on transactions carried out at physical branches and through online/digital channels.

Retail Industry

Sales data in a retail company can include various types of information related to the products sold, customers, timing of sales, and sales channels. Here’s how that data might look:

  • Product information: SKU (stock keeping unit), product name, product category, product price, quantity sold.
  • Customer information: Customer ID, customer demographics (age, gender, location, etc.), customer behavior (purchase frequency, preferred shopping time, preferred shopping channel, etc.), customer loyalty status (regular, VIP, etc.)
  • Sales information: Sales ID, date and time of sale, sales channel (online, in-store), sales region, total sale amount, promotional offers applied.
  • Inventory information: Stock levels at the time of sale, reordering levels and frequency, product returns, and reasons for return.

Sales Data Solutions for Every Member of the Sales Team

Here’s how a revenue intelligence solution can empower everyone in your team:

CSOs and VPs

Around 71% of VPs don’t feel confident that they can respond to the changing sales space quickly enough. Revenue Intelligence helps sales orgs rapidly adjust to market conditions by showing which sales activities are selling best. This also makes it easy to continually test and improve the sales strategy.

Another benefit of Revenue Intelligence for VPs and CSOs is that it makes forecasts of future revenue more reliable by comparing current deals to trends from historic won and lost deals and showing which deals are likely to actually close. Reliable forecasts help CSOs steer the ship so they invest when they can without overspending.

Sales Managers and Directors

Sales Managers and directors need serious visibility of the sales process. Revenue Intelligence collects and organizes sales data to show how deals are progressing, how reps are selling, and where the sales processes are being implemented and giving good results. With data delivered in real-time, managers can see first-hand when a deal might be going south and help reps turn it around.

Revenue Intelligence takes extra strain off managers in the modern workplace by providing guidance and assistance to teams when they need an extra nudge in the right direction. And since data is collected automatically, managers spend less time asking reps how things are going.

Sales Operations

75% of Sales Ops feel overwhelmed by new responsibilities in their workplace. With Revenue Intelligence, Sales Ops get additional support to address the new challenges of organizing and reinforcing the sales strategy. Revenue Intelligence analyzes communications data and compares it to won and lost deals to show which sales activities perform best.

Sales data can also be the key to improving the onboarding process for Sales Ops. Ramp-up time can be reduced by around 42% by allowing Sales Ops to send reminders to reps about how to execute techniques from their training — right when needed. There’s also a positive feedback loop of data showing which processes are being used and which deliver the best results.

Sales Reps and AEs

Even modern sales reps and AEs benefit from the right sales data. These professionals often need extra guidance and support to help them achieve the best outcomes. Around 77% of sales reps struggle to keep up with their tasks, making it easy for outcomes to slip. Revenue Intelligence helps reps prioritize actions by showing them what needs their attention and which activities will bring the best results.

In modern sales, getting valuable data to help close deals can be like taking a drink from a firehose. Revenue Intelligence automatically signals reps about the best next steps to take and provides insights about what will close more deals.


1. How Do You Use Sales Data in Modern Business?

Modern businesses have access to a wide range of sales data, including transactional data, customer interactions data, and behavioral data. They can use advanced technologies like CRM systems to automatically collect and organize sales data in a structured and meaningful way. Moreover, these systems often use cloud-based storage, ensuring data accessibility, security, and scalability.

Additionally, data analytics tools can sift through vast amounts of sales data to identify patterns, correlations, and trends. For instance, businesses can discover which products or services are selling well, at what times, and in which locations. They can also identify which marketing efforts are leading to the most conversions. Machine learning and AI can even be used for predictive analytics, helping businesses anticipate customer behavior and adjust their strategies accordingly.

2. Why is Sales Data Important?

Knowing how your business is performing is crucial. Sales data gives you an accurate picture of this performance. With it, you can see which products are popular, identify sales trends, and predict future sales. It’s like having a road map for your business.

3. How Do You Analyze Sales Data?

There’s no one-size-fits-all approach. But typically, you can start by looking at overall sales figures. Then, dig deeper into individual products or customers. Graphs and charts can help you spot patterns and trends. Some businesses use software tools to make the analysis process easier.

How sales data accuracy will impact your sales team?

Harnessing the power of data to supercharge sales isn’t a novelty. To stay in the competitive loop, companies need to embrace data-driven sales and evolve their strategies in tandem with market transformations.

When it comes to using your sales data in a potent way, keep this in mind: revenue intelligence. With Revenue Signals lying in the heart of revenue intelligence framework, your sales data can be transformed into a powerful tool that strengthens your sales team.

Our latest white paper delves into the power of using sales data to boost your sales team’s performance and overcome revenue leaks in your sales pipeline.

Check out our latest white paper here